Title :
Fault Locating of Grounding Grids Based on Ant colony Optimizing Elman Neural Network
Author :
Zhipeng, Yi ; Minfang, Peng ; Hao, He ; Xianfeng, Liu
Author_Institution :
Hunan Univ. of Electr. Eng., Changsha, China
fDate :
July 31 2012-Aug. 2 2012
Abstract :
In order to improve the accuracy and efficiency of the fault location of grounding grids, a new method combing ant colony algorithm (ACA) with Elman neural network is proposed. The method contrasts the voltages of the test points when the grounding grids is normal or not. The simulation results showes that the method can save time and improve accuracy.
Keywords :
ant colony optimisation; earthing; fault location; power grids; recurrent neural nets; ACA; Elman neural network; ant colony algorithm; fault location; grounding grids; Biological neural networks; Conductors; Fault diagnosis; Grounding; Training; Vectors; Elman neural network; ant colony algorithm; fault locating; grounding grids;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
DOI :
10.1109/ICDMA.2012.97
